Merging FNGS

BNU1

Sanity Check

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_2mm_0503/BNU1/aal-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 2
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]
  
  signal_overall <- c(signal)
  ids_overall <- c(ids)
  dataset_overall <- c(rep('BNU1', times=length(signal)))

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

## Warning: package 'reshape2' was built under R version 3.3.3

## Warning: package 'ggplot2' was built under R version 3.3.3

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(abs(cor(ts1)), title=title, legend="corr"))

Non Ranking

Spectral Approach

Raw Amplitude Spectrum

  tr = 2.0
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- data.frame(dataset='BNU1',
                           postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d))

DC1

Non Ranking

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_2mm_0503/DC1/aal-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 2
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]
  
  signal_overall <- c(signal_overall, signal)
  ids_overall <- c(ids_overall, ids)
  dataset_overall <- c(dataset_overall, rep('DC1', times=length(signal)))

Sanity Check

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(abs(cor(ts1)), title=title, legend="corr"))

Spectral Approach

Raw Amplitude Spectrum

  tr = 1
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- rbind(collection, data.frame(dataset='DC1',
                                             postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d)))

LMU3

Non Ranking

  inpath <- 'C:/Users/ebrid/Documents/R/fngs_2mm_0503/LMU3/aal-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 2
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]
  
  signal_overall <- c(signal_overall, signal)
  ids_overall <- c(ids_overall, ids)
  dataset_overall <- c(dataset_overall, rep('LMU3', times=length(signal)))

Sanity Check

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(abs(cor(ts1)), title=title, legend="corr"))

Spectral Approach

Raw Amplitude Spectrum

  tr = 3
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- rbind(collection, data.frame(dataset='LMU3', postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d)))

UWM

Non Ranking

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_2mm_0503/UWM/aal-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 2
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]
  
  signal_overall <- c(signal_overall, signal)
  ids_overall <- c(ids_overall)
  dataset_overall <- c(dataset_overall, rep('UWM', times=length(signal)))

Sanity Check

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(abs(cor(ts1)), title=title, legend="corr"))

Spectral Approach

Raw Amplitude Spectrum

  tr = 2.6
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- rbind(collection, data.frame(dataset='UWM', postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d)))

NYU1

Non Ranking

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_2mm_0503/NYU1/aal-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 2
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]
  
  signal_overall <- c(signal_overall, signal)
  ids_overall <- c(ids_overall)
  dataset_overall <- c(dataset_overall, rep('NYU1', times=length(signal)))

Sanity Check

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(abs(cor(ts1)), title=title, legend="corr"))

Spectral Approach

Raw Amplitude Spectrum

  tr = 2
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- rbind(collection, data.frame(dataset='NYU1', postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d)))

HNU1

Non Ranking

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_2mm_0503/HNU1/aal-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 2
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]
  
  signal_overall <- c(signal_overall, signal)
  ids_overall <- c(ids_overall)
  dataset_overall <- c(dataset_overall, rep('HNU1', times=length(signal)))

Sanity Check

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(abs(cor(ts1)), title=title, legend="corr"))

Spectral Approach

Raw Amplitude Spectrum

  tr = 2
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- rbind(collection, data.frame(dataset='HNU1',
                                             postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d)))

  collection$dataset <- factor(collection$dataset)
  collection$postprocessing <- factor(collection$postprocessing)
  summaryfig <- ggplot(collection, aes(x=postprocessing, y=discr, color=dataset)) +
    geom_point(size=4) +
    ggtitle('Comparing Discriminability over 4 reference datasets')
  print(summaryfig)

  summaryfig <- ggplot(collection, aes(x=postprocessing, y=discr, fill=postprocessing)) +
    geom_violin() +
    geom_boxplot(width=0.1) +
    ggtitle('Comparing Discriminability over 4 reference datasets')
  print(summaryfig)